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. Author manuscript; available in PMC: 2022 Feb 1.
Published in final edited form as: Soc Sci Med. 2020 Dec 29;270:113663. doi: 10.1016/j.socscimed.2020.113663

Randomized Controlled Trial of a Breast Cancer Survivor Stories Intervention for African American Women

Tess Thompson 1, Maria Pérez 2, Yan Yan 2, Matthew W Kreuter 1, Julie A Margenthaler 2, Graham Colditz 2, Donna B Jeffe 2
PMCID: PMC8173764  NIHMSID: NIHMS1697968  PMID: 33454539

Abstract

Rationale:

Video-based interventions hold promise for improving quality of life (QoL) among African American breast cancer patients.

Objective:

An interactive, cancer-communication intervention using African American breast cancer survivors’ narratives was tested in a randomized controlled trial to determine whether viewing survivor stories improved newly diagnosed African American breast cancer patients’ QoL.

Method:

Participants were 228 African American women with non-metastatic breast cancer interviewed five times over two years; 120 controls received standard medical care, and 108 intervention-arm participants also received a tablet-computer with survivor stories three times in 12 months. Growth curve models were used to analyze differences between arms in change in eight RAND 36-Item Health Survey subscales, depressive symptoms, and concerns about recurrence. Additional models explored the effects of intervention usage and other intervention-related variables on QoL among patients in the intervention arm.

Results:

Models showed no effect of study arm on QoL, depressive symptoms, or concerns about recurrence. Longer use of the intervention was associated with an increase in concerns about recurrence and decline in three QoL subscales: emotional wellbeing, energy/fatigue, and role limitations due to physical health.

Conclusion:

Although no significant impact of the intervention on QoL was observed when comparing the two study arms, in the intervention arm longer intervention use was associated with declines in three QoL subscales and increased concerns about recurrence. Women with improving QoL may have interacted with the tablet less because they felt less in need of information; it is also possible that encouraging patients to compare themselves to survivors who had already recovered from breast cancer led some patients to report lower QoL. Future work is warranted to examine whether adding different stories to this cancer-communication intervention or using stories in conjunction with additional health promotion strategies (e.g., patient navigation) might improve QoL for African American breast cancer patients.

Keywords: breast neoplasms, health communications, African Americans, quality of life, randomized controlled trial, United States

Breast cancer is the most commonly diagnosed non-skin cancer among African American women (Siegel et al., 2020). Although incidence rates for breast cancer are 3% lower for African American women compared to White women, African American women tend to be diagnosed with more advanced-stage disease, and mortality from breast cancer is 41% higher for African American women compared to White women (DeSantis et al., 2019). As a result, only 81% of African American women diagnosed with breast cancer survive five years, compared to 91% of White women (DeSantis, 2019). African American patients are less likely to choose or receive guideline-adherent treatment or follow-up care (Advani et al., 2014, Roberts et al., 2015) and are more likely to have triple-negative breast cancers with a relatively poor prognosis (DeSantis et al., 2019).

As with other health disparities faced by African American women, disparities in breast cancer outcomes are driven by many factors, including structural racism, gender discrimination, socioeconomic adversity, and unequal access to high-quality care (Gerend and Pai, 2008; Geronimus et al., 2006, Ko et al., 2020; Phelan and Link, 2015; Roberts, 2011; Williams et al., 2016). The cumulative effect of these overlapping social, economic, and political factors makes it especially important to develop interventions to reduce health disparities and improve health outcomes for African American women (Williams et al., 2016). Many African American women live and work in environments that do not provide adequate access to accurate health information, and they seldom receive culturally competent health information designed especially for them (Eddens et al., 2009; Husain et al., 2018; Institute of Medicine, 2003; Viswanath and Kreuter, 2007; Wells et al., 2014). We describe here the results of a randomized controlled trial of an intervention designed to improve quality of life (QoL) in African American women newly diagnosed with breast cancer by disseminating authentic stories from African American breast cancer survivors.

QoL is an important indicator of wellbeing that has been linked to survival and other outcomes in breast cancer patients (DuMontier et al., 2018). In a cohort study in a predominantly white sample, patients with ductal carcinoma in situ (DCIS, stage 0) and early-invasive breast cancer (EIBC, stages 1–2A) reported lower QoL compared to same-aged controls 4–6 weeks after patients’ definitive surgical treatment or controls’ benign/negative screening mammogram (Jeffe et al., 2012). At 2-year follow-up, DCIS patients’ QoL was not significantly different from controls, but EIBC patients’ physical functioning and general health remained lower than that of controls (Jeffe et al., 2012). Patients in this cohort who received adjuvant chemotherapy reported worse QoL than patients who did not, regardless of the type of surgery received, and QoL did not rebound until after treatment (Jeffe et al., 2016).

Findings about QoL in African American women with breast cancer have been mixed. In the Women’s Health Initiative-Observational Study, lower general health and physical functioning was reported by African American than White patients with a breast cancer history, although the effect sizes were small (Paskett et al., 2008). Another longitudinal study found no physical or mental QoL differences between African American and White women in the five years after diagnosis, although the authors note that mean physical and mental health QoL scores at all time points in this low-income sample were lower than general U.S. population norms (Maly et al., 2015). Among Medicare beneficiaries of varied racial/ethnic backgrounds, QoL decreased after a cancer diagnosis compared to controls who did not have a new cancer diagnosis. This study also showed that racial/ethnic disparities in QoL that existed before a cancer diagnosis narrowed over time, possibly due to all patients receiving cancer care covered by Medicare managed care programs (Pinheiro et al., 2015).

Few studies have examined interventions to improve QoL specifically among African American breast cancer patients (Coughlin et al., 2015), particularly interventions addressing multiple QoL domains (Mollica and Nemeth, 2015). Some interventions have been tested or shown benefits in both Black and White women. A group cognitive-behavioral stress-management intervention provided to a primarily White sample of breast cancer survivors significantly reduced depressive symptoms over long-term follow-up (Stagl et al., 2015a, Stagl et al., 2015b). That intervention was adapted for use among African American breast cancer survivors (Lechner et al., 2013), but results of a randomized trial comparing the culturally appropriate cognitive-behavioral intervention to a comparison group receiving culturally appropriate education found that both groups showed significant improvements in QoL, stress levels, and depressive symptoms over a six-month period (Lechner et al., 2014). A small, single-arm study of a community-based intervention to promote social support and physical activity among African American breast cancer survivors found that strength, fitness, and QoL increased and depressive symptoms decreased (Nock et al., 2015). In addition to these face-to-face interventions, QoL interventions for African American women have been successfully delivered via telephone (Ashing and Miller, 2016), and an uncertainty-management intervention delivered via telephone combined with audiotapes or CDs showed benefits for both African American and White women (Germino et al., 2013, Gil et al., 2006, Mishel et al., 2005).

Narrative Theory and Research

Narrative interventions hold promise for health promotion among the general population (Hinyard and Kreuter, 2007) and cancer survivors (Kreuter et al., 2007). Breast cancer patients draw support from a range of sources, including from stories of other women who have survived breast cancer (Wells et al., 2014). Breast cancer initiatives such as the longstanding Reach to Recovery program are built around survivors sharing their experiences to increase awareness of cancer and use of cancer screening, and to provide support and hope to other cancer patients (Rogers et al., 1985). When people experience a stressor such as cancer, “experientially similar others” may offer information and encouragement, serve as role models, and provide hope for the future (Gage, 2013; Thoits, 2011). This social comparison to those who have had similar experiences also has the potential to provoke negative reactions, however, if people compare themselves to those who are better off (Gage, 2013). In addition to the benefits of learning from others, sharing stories provides an opportunity for cancer survivors to “give back” by helping others understand the complexities of cancer screening, diagnosis, and treatment (Wells et al., 2014). At the same time, cancer survivors who are racial/ethnic minorities may be underrepresented in online narrative content (Eddens et al., 2009).

Use of narratives for health promotion is consistent with the theoretical frameworks of Social Cognitive Theory (Bandura, 2001), which describes how people learn to change their behaviors through observing and interacting with others in their environment, and Transportation Theory (Green and Brock, 2002), which holds that narrative interventions may be especially effective when people are highly engaged and thus “transported” into stories. According to Transportation Theory, this absorption in a narrative leads to identification with characters and reduces counter-arguing, which leaves the audience more open to persuasion (Green and Brock, 2002). Building on these theories, Moyer-Guse emphasized how features of narratives including enjoyment and perceived similarity may help overcome people’s resistance to health messages (Moyer-Guse, 2008). These theories highlight the importance of audience identification with story characters, as communication strategies are more effective when the messenger, or person presenting information, is seen as similar to the viewer (Hinyard and Kreuter, 2007). Videos may be effective strategies for delivering health information because they focus the viewer’s attention on the source’s (e.g., cancer survivor’s) characteristics (Hinyard and Kreuter, 2007, Kreuter et al., 2007). Video stories may be most effective when the persons presenting information are seen as likable or trustworthy (Kreuter et al., 2007, McQueen et al., 2011).

Videos have been used as a health communication strategy for reaching African American audiences. A narrative smoking-cessation video developed for low-income African American smokers (Houston et al., 2011) increased immediate intentions to quit among randomized trial participants, although it did not lead to significant differences in smoking cessation (Cherrington et al., 2015). Videos of African American survivor stories were developed to promote screening mammography among African American women (Kreuter et al., 2010). African American women were randomized to watch either the video of breast cancer survivors’ narratives or an informational video presented by a “professional.” The narrative and informational videos had comparable effects on screening mammography at 6-month follow-up; however, participants who watched the narrative video reported stronger identification with and emotional reactions to the information source (Kreuter et al., 2010; McQueen & Kreuter, 2010; McQueen et al., 2011). Stratified analyses showed increased screening among women with fewer years of formal education in the narrative arm compared with the informational-video arm, providing preliminary evidence that narratives may help promote targeted behavior change among women with lower education (Kreuter et al., 2010).

The Current Study

Given the unique vulnerabilities of African American women with breast cancer (Gerend and Pai, 2008; Williams et al., 2016), this study tested a novel, interactive cancer-communication created to improve their QoL. We sought to determine whether a survivor stories intervention affected patients’ QoL, depressed mood, and concerns about recurrence. We hypothesized that, compared to women receiving only standard medical care recommended by their physicians, women also receiving the intervention would report greater improvement in QoL (the primary aim), as well as lower levels of depressed mood and fewer concerns about recurrence (exploratory aims). We also explored whether, among participants in the intervention arm, identification with storytellers and time spent using the intervention were associated with changes in QoL, depressed mood, and concerns about recurrence.

Methods

Participants in this parallel randomized controlled trial were newly diagnosed, African American breast cancer patients being treated at Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine or at Saint Louis University School of Medicine. Women were invited to participate via letter. Eligibility criteria were self-identification as an African American woman, 30 years of age or older, with a first primary, non-metastatic breast cancer (Stages 0–3). Exclusion criteria were prior breast cancer history, metastatic breast cancer, planned receipt of bilateral mastectomy, having mental or cognitive problems that would impede responding reliably to interview questions, and being unable to speak or understand English. Patients with a prior breast cancer history were excluded due to their prior experiences dealing with a breast cancer diagnosis and treatment. Patients with metastatic cancer were excluded because we expected them to have shorter median overall and breast cancer-specific survival (i.e., less than two years [Dawood et al., 2008]) than patients with Stages 0–3 breast cancer. Patients planning to receive a bilateral mastectomy were excluded because one of the outcomes of interest was adherence to surveillance mammography, recommended only for patients who have had breast-conserving surgery or unilateral mastectomy (Runowicz et al., 2016). The study was approved by the Institutional Review Board at both sites. Participants provided informed consent and received $25 per interview.

All participants (120 in the control arm, 108 in the intervention arm) received standard medical care. Participants in the intervention arm also received the intervention, an interactive video program loaded on a touch-screen tablet computer. All participants completed five interviews: Interview 1 (baseline, near the time of a post-operative visit or, for eligible patients, near the start of neoadjuvant therapy); Interview 2 (one month after baseline); Interview 3 (six months after definitive surgical treatment); Interview 4 (12 months after surgical treatment); and Interview 5 (24 months after surgical treatment). Attrition over the study is reported in Figure 1. The trial ended once recruitment for the target sample size was reached and two years of follow-up were completed.

Figure 1.

Figure 1.

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CONSORT Flow Diagram between December 2009 and January 2015 (Jarvandi et al., 2020).

Intervention

Participants in the intervention arm received the Survivor Stories intervention three times in the year after enrollment. This new intervention—which drew from Transportation Theory (Green and Brock, 2002) and Social Cognitive Theory (Bandura, 1977; Bandura, 2001) as well as the authors’ longstanding community partnerships with local breast cancer support groups for African American women—used African American breast cancer survivors’ stories to share accurate health information about breast cancer treatment and survivorship. Transportation Theory holds that when viewers are more engaged, or “transported” into a story (in this case, the survivors’ narratives), they are more receptive to the story’s content (Green and Brock, 2002). African American patients might identify with survivors, vicariously learn from their experiences, and make behavioral choices as appropriate to their own circumstances, breast cancer diagnosis, and treatment recommendations to improve their own QoL (Bandura, 2001).

Storytellers were 35 African American breast cancer survivors between the ages of 32 and 68 who were recruited through our community partnerships (Kreuter et al., 2010). A semi-structured interview guide based on Wengraf’s (2011) biographic narrative interview method was used to elicit storytellers’ personal experiences with breast cancer; at the time of recording, they had been survivors from 4–30 years. The intervention was an interactive, tablet computer-based video program created using 207 clips of stories (1–3 minutes each) from these interviews that addressed 12 breast cancer topics. These topics focused on aspects of coping, support and relationships, healthcare experiences, follow-up care, QoL, and treatment side effects. The video program also contained a dictionary of terms about breast cancer diagnosis, treatment, side effects, and recovery. Development and pilot testing of the video program (Pérez et al., 2014) and detailed information about the intervention (Pérez et al., 2020) are reported elsewhere.

Research team members (who did not self-identify as African American) provided participants in the intervention arm with a printed user guide and in-person training to properly use the tablet and navigate video program. Thus, neither the participants nor research-team members were blinded to group assignment. The first intervention exposure (Exposure 1) occurred between Interviews 1 and 2. Study participants could choose how often and how much they used the tablet and could search for stories by storyteller or by story topic. Exposure 2 occurred approximately three weeks before Interview 3, and Exposure 3 occurred approximately three weeks before Interview 4. At each exposure, a study staff member called participants about one week after intervention delivery to troubleshoot any problems, and again a week later to schedule the next interview and a time to return the tablet. Each exposure was intended to last about two weeks. Of the 108 intervention arm participants, 107 received the tablet at least once (see Figure 1).

Measures

The main outcome of interest for these analyses was QoL, with exploratory analyses examining depressed mood and concerns about recurrence. These measures were completed by participants at each time point. Intervention arm participants were also assessed on usage of and reaction to the intervention after every intervention exposure.

QoL.

QoL was assessed at every interview with the eight subscales of the RAND 36-item Health Survey 1.0 (Hays et al., 1993): general health, physical functioning, role limitations due to physical health, role limitations due to emotional problems, energy/fatigue, pain, emotional wellbeing, and social functioning. Some items were negatively worded, requiring reverse scoring before calculating subscale scores. Standardized subscale scores were computed with a mean of 50 and standard deviation of 10; higher scores indicate better QoL on each subscale (RAND Corporation, 2019). This measure has been shown to be reliable and valid in a range of populations (Wolinsky et al., 2004). Ranges of Cronbach’s α for subscales across interviews were physical functioning, .90–.94; role limitations/physical, .80–.94; emotional wellbeing, .85–88; energy/fatigue, .80–.86; role limitations/emotional, .85–.89; pain, .79–.88; social functioning, .78–.85, and general health, .71–.77.

Center for Epidemiologic Studies Depression Scale (CES-D).

The 20-item CES-D measured depressive symptoms in the past week (Radloff, 1977) at every interview. The CES-D has shown good reliability and validity in various samples (Ashing-Giwa and Rosales, 2013, Radloff, 1977). Scores range from 0 – 60; higher scores indicate greater depressed mood. Cronbach’s α across interviews was .92–.94.

Concerns about Recurrence Scale (CARS).

The first four items of the Concerns about Recurrence Scale measured the extent of patients’ concerns that their cancer would recur (Vickberg, 2003) at all interviews. Responses used a 6-point scale ranging from 1 (not at all) to 6 (all of the time); higher mean scores indicate greater severity of concerns about recurrence. Cronbach’s α across interviews was .93–.95.

Demographic covariates.

Age, employment, marital status, household income, insurance status, and education were self-reported at Interview 1. Education information was available for all participants, so education was included in the model as a measure of socioeconomic status (1 = education beyond high school, 0 = high school diploma/GED or less). Age was analyzed as a continuous variable; employment status was dichotomized (1 = working full/part-time, 0 = not working full or part-time), as was marital status (1 = currently married/partnered, 0 = not married/partnered).

Clinical and psychosocial covariates.

Cancer stage was based on clinical staging and surgical pathology and was dichotomized for analysis into early (stage 0, 1 or 2A) or locally advanced (stage 2B or 3). Treatment information, obtained from interview and the medical record, included type of surgery (breast-conserving surgery vs. mastectomy) and whether participants received hormone therapy, radiation therapy, and chemotherapy (1 = yes; 0 = no). Because surgery type was significantly correlated with stage and receipt of radiation therapy, and three participants did not receive definitive surgical treatment, surgery type was not included in multivariate models. Comorbidity was assessed with the Charlson comorbidity index (Charlson et al., 1987) adapted for interviews (Katz et al., 1996); higher scores (ranging from 0–31) indicate more severe comorbidity.

History of depression was based on a “Yes” response to at least one of two questions: “Has a doctor ever told you that you had depression?” or “Have you ever been treated for depression with medication or psychotherapy?” Perceived social support was measured using the 19-item Medical Outcomes Study Social Support Survey (MOS-SSS) (Sherbourne and Stewart, 1991) measuring perceived availability of social support. Higher scores indicate greater perceived support. Baseline MOS-SSS scores were included in the models (Cronbach’s α = .97).

Intervention-related variables.

Intervention-related variables were included in models for the intervention arm only. The number of minutes that patients used the intervention at each exposure was based on tablet logs; number of minutes excluding training was used to reflect the amount of time participants used the tablet on their own. A latent “usage” variable was created that incorporated the number of minutes participants used the intervention at each of the three exposures; higher values reflect longer use of the tablet.

Identification with the storytellers was assessed using a 7-item subscale measuring perceived similarity to the storytellers and a 4-item subscale measuring trust in the storytellers (see Online Supplement 1). Identification item responses used a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). Mean scores were computed for each subscale. Identification items were assessed at Interviews 2, 3, and 4 after each exposure. Subscale scores for similarity and trust measured at Interview 2 (after Exposure 1) are included in the models. Cronbach’s α at Interview 2 was .89 for perceived similarity and .78 for trust in the storytellers.

Emotional reactions to videos were assessed using a four-item measure of positive reactions and an eight-item measure of negative reactions developed from items used in a prior study (McQueen & Kreuter, 2010, McQueen et al., 2011, Pérez et al., 2020) and assessed at Interviews 2, 3, and 4. Response options ranged from 1 (not at all) to 5 (extremely), with higher scores indicating higher levels of emotional reactions. Positive and negative subscale scores measured at Interview 2 (after Exposure 1) are included in the models. Cronbach’s α at Interview 2 was .80 for positive reactions and .90 for negative reactions.

Analysis Plan

Intention-to-treat analyses were conducted. Sample size determination is reported in Online Supplement 1. Descriptive and bivariate analyses were conducted with IBM SPSS Statistics 24.0 (Armonk, NY: IBM Corp.). Differences between study arms in outcome variables were determined using growth curve models (Bollen and Curran, 2006), a flexible form of structural equation modeling that can be used to model change in variables with at least three waves of data. The robust maximum likelihood estimator (MLR) in Mplus 7.0 (Los Angeles, CA: Muthén & Muthén) was used for growth curve models.

For each outcome variable, unadjusted and adjusted one-group models controlling for study arm were used to determine whether there were significant differences in QoL trajectories between the two arms (Bollen and Curran, 2006). Growth curve models estimate two latent variables: intercept (average estimated starting point) and slope (change over time). Because participants were randomly assigned to arms, baseline outcome measures were expected to be equivalent between arms, and the association between study arm and slope was of primary interest. A significant association between study arm and slope would indicate an intervention effect for that outcome over time. Additional unadjusted and adjusted models were conducted within the intervention arm to explore whether intervention-use experiences—including number of minutes spent using the intervention, identification with storytellers (i.e., similarity and trust), and positive and negative emotional reactions to the stories—affected QoL, depressed mood, and concerns about recurrence.

Missing data.

Very few predictor variables (i.e., variables measured at Interview 1 or intervention-related variables measured at/after Exposure 1) were missing data. Two participants were excluded from adjusted models due to missing treatment predictors (one was missing data about radiation therapy, hormone therapy, and chemotherapy; another was missing data about hormone therapy only), for a total sample of 226. Data missing at Interviews 2–5 due to attrition or nonresponse were estimated using the robust maximum likelihood (MLR) function in Mplus. Maximum likelihood estimation of missing data is preferable to listwise deletion because it allows for the use of all available data (Graham, 2009). Analyses in the intervention arm only included the 104 participants who provided data about reactions to the intervention at Interview 2 (after Exposure 1). Missing data from Interviews 3–5 due to attrition or nonresponse was estimated using the MLR estimator. Missing data about tablet use at Exposures 2 and 3 was handled by creating a latent “usage” variable that incorporated the number of minutes the tablet was used at Exposures 1–3; this allowed estimation of missing data for this variable using maximum likelihood.

Modifications of Preplanned Analyses

The analysis plans in the original study protocol were modified by the study team in two ways (Online Supplement 1), consistent with the preregistration described at ClinicalTrials.gov (Study Identifier: NCT00929084).

Outcome Measures.

Aim 1 of this study sought to determine whether and to what extent African American breast cancer survivor stories affected various aspects of QOL, depressed mood, and concerns about recurrence among African American breast cancer patients during and after primary treatment. For sample size determination, we considered QoL the primary outcome and adherence to surveillance mammography the secondary outcome (Online Supplement 1). The alpha level was originally set at 0.025 to test two hypotheses (the effect of the intervention on total Functional Assessment of Cancer Therapy-Breast score [FACT-B (Brady et al., 1997)], the primary outcome, and on receipt of at least one surveillance mammogram by 2-year follow-up, the secondary outcome). For several reasons described in Online Supplement 1, however, we ultimately opted to replace the FACT-B and used the eight subscales of the RAND-36 to measure QoL. We therefore divided the planned alpha level by eight to account for multiple tests, setting the significance level at p < .003 for tests of all RAND-36 subscales. All other analyses, including those using the CES-D and CARS as outcomes and those examining intervention-related variables, were considered exploratory and had an alpha level of p < .05.

Analytic changes.

Consistent with prior longitudinal analyses of this dataset (Thompson et al., 2017, 2019), growth curve models were used to test differences between study arms instead of Generalizing Estimating Equations as stated in the protocol (see Online Supplement 1). Growth curve models provide a flexible means for analyzing change in a construct over time and enable modeling of both group and individual trajectories (Bollen and Curran, 2006, Skrondal and Rabe-Hesketh, 2004); this allowed us to test QoL outcomes based on study arm and also conduct exploratory analyses of the effects of intervention-related variables in the intervention group. Effect sizes were calculated as described by Feingold (Feingold, 2015, Feingold, 2013). Missing data were estimated using maximum likelihood rather than multiple imputation; both strategies are acceptable methods for handling missing data (Graham, 2009).

Results

Between December 2009 and December 2012, 397 women were assessed for eligibility (see Figure 1). Of these, 243 were randomly assigned to one of two arms with a 1:1 allocation. A total of 228 eligible participants consented, enrolled, and completed the baseline interview; follow-up interviews were completed in January 2015. Table 1 provides information about baseline demographic, psychosocial, and cancer-related variables. There were no significant differences in these variables between study arms. The majority of participants reported household income below $25,000; over half were not employed and not married/partnered. Most had early-stage breast cancer and received breast-conserving surgery.

Table 1.

Baseline descriptive statistics for Survivor Stories participants, by study arm (N = 228).

Variable Intervention (n = 108) Mean (SD) or n (%) Control (n = 120) Mean (SD) or n (%) p
Married/partnered
 Yes 27 (25.0%) 37 (30.8%) .377
 No 81 (75.0%) 83 (69.2%)
Employed
 Full/part-time 48 (44.4%) 53 (44.2%) 1.000
 Not employed 60 (55.6%) 67 (55.8%)
Household income
 Below $25,000 65 (60.7%) 67 (57.8%) .684
 $25,000 or more 42 (39.3%) 49 (42.2%)
Insurance
 Some private 44 (41.1%) 57 (49.6%) .226
 Public/no insurance 63 (58.9%) 58 (50.4%)
Education
 ≤High school 56 (51.9%) 52 (43.3%) .232
 Beyond high school 52 (48.1%) 68 (56.7%)
History of depression
 Yes 36 (33.3%) 45 (37.5%) .580
 No 72 (66.7%) 75 (62.5%)
Age 55.8 (9.7) 56.0 (10.3) .870
Comorbidity 1.1 (1.6) .9 (1.2) .326
Social support 83.6 (18.6) 80.6 (20.8) .252
Hormone therapy
 Yes 70 (64.8%) 72 (61.0%) .584
 No 38 (35.2%) 46 (39.0%)
Chemotherapy
 Yes 53 (49.1%) 59 (49.6%) 1.000
 No 55 (50.9%) 60 (50.4%)
Radiation therapy
 Yes 83 (76.9%) 93 (78.2%) .874
 No 25 (23.1%) 26 (21.8%)
Stage
 Early 80 (74.1%) 85 (70.8%) .657
 Locally advanced 28 (25.9%) 35 (29.2%)
Surgery
 Breast-conserving 71 (67.0%) 84 (70.6%) .568
 Mastectomy 35 (33.0%) 35 (29.4%)
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Note: p-values derived from two-tailed independent sample t-tests or chi-square/Fisher’s Exact tests. Number of participants with missing data: Income 1 intervention, 4 control; Insurance, 1 intervention, 5 control; radiation therapy, 1 control; hormone therapy, 2 control; chemotherapy, 1 control. Three participants (2 intervention, 1 control) did not have definitive surgical treatment.

Table 1S (Online Supplement 2) provides data for the 10 outcome variables at every interview. None of the differences between arms in outcome variables at any of the interviews were below the significance threshold set for subscale outcome variables (p < .003). There was, however, a baseline difference (p < .05) in the role limitations/emotional subscale by arm (p = .029); participants in the intervention arm had a lower mean score than the control arm.

Table 2S (Online Supplement 2) provides descriptive information for intervention-related variables for all interviews, including number of minutes using the tablet, measures of identification (similarity and trust subscales), and positive and negative emotional reactions. At Exposure 1, mean tablet usage of participants on their own was 131 minutes (SD = 117). At Exposure 2, mean tablet usage was 57 minutes (SD = 76), and at Exposure 3 it was 55 minutes (SD = 77). Participants who received the intervention at all three exposures used the tablet on their own an average 259 minutes total (range 0 – 799, SD = 201).

In unconditional models in the overall sample, five QoL subscale scores increased over time (Online Supplement 2, Table 3S): role limitations due to physical health, role limitations due to emotional problems, energy/fatigue, emotional wellbeing, and social functioning (p < .05). Two subscales decreased: physical functioning and general health (p < .05). The pain subscale, depressive symptoms, and concerns about recurrence showed no significant change over time.

Results of adjusted outcome models are presented in Table 2; additional information about unadjusted and adjusted models, including p-values and fit statistics, is presented in Online Supplement 2 (Tables 4S and 5S). Unadjusted analyses examining the effect of the intervention on change in QoL subscale scores, depressed mood, and concerns about recurrence (Table 4S) show that study arm was not a predictor of slope for any of these outcomes, indicating a lack of intervention effect. These findings held in adjusted models (Tables 2 and 5S). Although the effect of study arm on slope in role limitations due to emotional problems was p < .05 in the adjusted model (estimate = 3.968, p = .017), it was not below the p < .003 threshold set to account for tests of multiple QoL subscales. In adjusted analyses for this subscale, there was a significant association (estimate = −11.440, p = .023) between study arm and intercept, indicating a difference between arms in this subscale at baseline. An additional post hoc, exploratory test included intercept as an additional covariate in the model predicting slope for this subscale; in this model, effect of study arm on change of role limitations due to emotional problems was attenuated (estimate = 2.439, p = .088).

Table 2.

Adjusted models showing unstandardized parameter estimates of effects of predictors on slope (change over time) for each outcome measure (N = 226).

Predictors Physical functioning Role limitation/physical Role limitation/emotional Energy/fatigue Emotional wellbeing Social functioning Pain General health CES-D CARS
Study arm (1 = video) .296 .663 3.968* −.356 .638 −.169 −.394 .242 −.523 .051
Covariates
Age −.090 −.027 −.183 −.111* −.074 −.144* −.122* −.084* .036 .004
Working −1.167 1.549 .712 .135 −.602 −1.716 −.159 −1.249 .508 .048
Married/partnered .892 3.376 3.903* .752 .641 2.308* 2.268* .206 −.529 −.003
Education > high school 1.109 .950 .008 .134 −.247 .239 1.871 .486 −.093 −.052
History of depression .144 −.307 1.322 .157 −.185 .240 −.755 .149 .058 −.013
Social support .035 .060 −.043 .010 −.040* −.016 −.035 .030 .011 .000
Late stage −3.868* −5.207* −2.501 −.492 −2.278* −2.377 −1.886 −.446 .840 .014
Hormone therapy −.466 −1.683 2.140 −.022 1.329 −.043 .452 −.481 −.540 −.070
Radiation therapy −.578 −.138 3.054 −1.083 −1.687* −1.004 −1.145 −.317 .476 .074
Chemotherapy 1.804 2.378 2.145 1.161 2.469* 2.642* 1.242 .768 −1.292* −.049
Comorbidity .187 −1.116 .140 .140 .290 .093 .145 .310 −.156 −.028
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*

p < .05;

**

p < .003 (significance level set to account for multiple tests)

Note: CES-D = Center for Epidemiologic Studies Depression scale. CARS = Concerns About Recurrence Scale

Exploring effects of intervention-related variables on patients in the intervention arm (see Table 3 and Online Supplement 2, Table 6S), we found that changes in QoL subscales, depressive symptoms, and concerns about recurrence were not significantly related to similarity to or trust in the storytellers or with positive emotional reactions to the stories. In unadjusted analyses, watching videos longer was associated with steeper decreases in scores for role limitations due to physical health, energy/fatigue, and emotional wellbeing, as well as increased concerns about recurrence. Reporting more negative emotional reactions to stories was associated with greater decrease in depressive symptoms (estimate = −.821, p = .002). Most of these effects held in adjusted analyses. The exceptions were the association between time watching videos and energy/fatigue, which became non-significant when covariates were added (estimate = −.016, p = .209), and the association between time watching videos and role limitations due to emotional health, which became significant when covariates were added (estimate = −.083, p = .046).

Table 3.

Unadjusted exploratory models showing unstandardized parameter estimates of effects of intervention-related variables on slope (change over time) for each subscale, CES-D, and CARS in participants in the intervention arm (N = 104).

Variables Physical funct Role lim/physical Role lim/emotional Energy/fatigue Emo wellbeing Social funct Pain Gen health CES-D CARS
Usage −.012 −.053* −.079 −.030* −.027* −.045 −.020 −.015 .008 .002*
Identification (similarity) .469 −.878 −2.515 −.300 −.041 .546 .464 −.225 .307 −.039
Identification (trust) 1.870 .617 −.797 −.137 −.917 −.294 1.463 1.167 −.412 .007
Positive emotion .077 .180 1.204 .254 .164 −.149 −.974 −.215 .108 .010
Negative emotion .285 −1.390 1.179 −.354 1.107 .732 −.651 .260 −.821* .026
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Note: funct = functioning; lim = limitations; CES-D = Center for Epidemiologic Studies Depression scale; CARS = Concern About Recurrence Scale

*

p < .05

Discussion

African American women face profound health disparities in the U.S., including unique challenges across the cancer care continuum (Gerend and Pai, 2008; Williams et al., 2016). This randomized controlled trial tested a novel health communication intervention to improve QoL in African American women with breast cancer. The survivor stories included in the intervention provided newly diagnosed breast cancer patients the opportunity to learn from a group of “experientially similar others” (Thoits, 2011) three times in the year after a breast cancer diagnosis. Our main hypotheses were not supported; we saw no significant differences between the intervention and control arms in QoL, depressive symptoms, or concerns about recurrence. However, exploratory analyses of participants in the intervention arm revealed that more time using the intervention was associated with an increase in concerns about recurrence, as well as declines in three QoL subscales: emotional wellbeing, energy/fatigue, and role limitations due to physical health.

Results of this study provide insight into QoL among African American breast cancer patients in the two years following diagnosis. In the overall sample, there were gains in five QoL subscales (role limitations due to physical health, role limitations due to emotional problems, energy/fatigue, social functioning, and emotional wellbeing) and declines in two (physical functioning and general health). Overall scores for several subscales (particularly role limitations/physical, role limitations/emotional, and pain) were lower than those previously seen in a predominantly White cohort of Stage 0–2A patients at this cancer center at baseline and two-year follow-up (Jeffe et al., 2012) and lower than those reported for African Americans within five years of a breast cancer diagnosis (Giedzinska et al., 2004). In addition, results from the intervention arm showed promise in terms of engagement, since participants used the video narrative intervention for over four hours on average across three exposures, although there was considerable variability in intervention use across participants.

The null trial results for the intervention suggest that narratives may not be effective as a stand-alone QoL intervention for African American breast cancer patients like those in our sample (i.e., predominantly low-income women with early-stage cancer). Our results are consistent with other studies that found no significant effect of a narrative DVD on smoking cessation (Cherrington et al., 2015) or of a narrative video on screening mammography uptake among African American women (Kreuter et al., 2010). Taken together, these results suggest that narrative interventions such as this, while acceptable and feasible (Pérez et al., 2020), may not provide benefits over and above benefits of other communication or behavioral interventions in some contexts. Given the amount of effort needed to develop and test a medically accurate video narrative intervention (Pérez et al., 2014), practitioners should consider whether narratives are the optimal strategy for improving QoL in breast cancer patients.

It is also possible that using different narratives at different times over the cancer continuum may be more effective in improving QoL for African American breast cancer patients. Our intervention offered the same stories at every exposure. As reported elsewhere (Pérez et al., 2020), videos focusing specifically on QoL were not watched very much at any of the three exposures; patients seemed interested in watching stories of immediate relevance, particularly stories about telling others about their diagnosis and dealing with treatment side effects early on. Adding or removing videos from the intervention over time, or including a wider range of topics, might lead to improvements in QoL throughout the treatment and survivorship trajectory. Videos pertaining to QoL, in particular, might be more relevant to participants if made available after treatment completion. Another explanation for lack of intervention effect could be that the vast majority of participants were treated at a National Cancer Institute-designated Comprehensive Cancer Center; in interviews with a subsample of married women from this study, participants mentioned being pleased with the care and support they received from doctors and staff at the cancer center and support from researchers conducting other studies (Thompson et al., 2018). An intervention effect might be observed in women with more limited access to care, support, and information resources from medical professionals and staff compared with the resources available to these participants. Moreover, attention from study staff during interviews may have provided participants in both arms with support that could have positively affected their QoL.

Exploratory analyses in the intervention arm found more minutes using the intervention was associated with a steeper decline in three QoL subscales and an increase in concerns about recurrence. Because participants decided how much to use the intervention, it is impossible to determine whether longer use of the videos led to lower QoL, or whether people whose QoL was declining used the intervention more. Women with improving QoL may have interacted with the tablet less because they felt less need for additional information; this pattern would be consistent with prior work showing that people use digital health communication resources less when they already feel well-informed or perceive themselves not to need them (Coorey et al., 2020; Varsi et al., 2013). It is also possible that encouraging social comparisons to women who have recovered from breast cancer made participants who used the tablet more feel they were not performing as well and led them to report lower QoL. Bouchard and colleagues (2019) found, for example, that among breast cancer patients, more frequent thoughts about being similar to women who had already recovered (i.e., upward identification) predicted more depressive symptoms six months later. Gage (2013) also found that parents of pediatric cancer patients reported that social comparisons to experientially similar others had drawbacks as well as benefits. In addition, research has suggested that passive social media use (e.g., watching videos) is associated with more severe depressive symptomatology (Escobar-Viera et al., 2018); encouraging people to share stories in a more active way (e.g., message boards) may promote better QoL.

Reporting higher negative emotional reactions to the stories at first viewing was associated with a decrease in depressive symptoms, which is intriguing in light of research suggesting that negative emotions, particularly sadness, may enhance message recall and increase its persuasiveness (Yoo et al., 2014). Negative emotional reactions may not be an undesirable response to health communication interventions, because they are associated with engagement and may indicate the audience’s empathy with storytellers who face difficult situations (McQueen & Kreuter, 2010). Future work should determine whether this association between negative emotional reactions and change in depressive symptoms can be replicated or leveraged to improve patients’ mental health. It is also possible that this finding is a regression to the mean in terms of overall negative affect; that is, people experiencing more negative affect around the time of diagnosis (i.e., people who had high levels of depressive symptoms and greater negative emotional reactions to the stories) may have been more likely to improve over time.

The low QoL scores observed for several subscales suggest the importance of continuing to investigate ways to improve QoL and other outcomes among African American women with breast cancer. Future work could examine whether different stories or strategies improve QoL for African American breast cancer patients. The current study focuses on preplanned analyses of QoL outcomes in a randomized controlled trial, but additional research could explore whether the intervention may have been effective for particular subgroups, whether it may be more effective to target patients who particularly need or want help addressing QoL issues, or whether there are intervention benefits not adequately captured by QoL measures. Future research also could examine the effects of integrating narrative elements into existing evidence-based interventions for breast cancer patients (Stagl et al., 2015a). It is possible that, in a predominantly low-income sample such as ours, enriching the information environment through health communication interventions alone is not sufficient to improve outcomes. It may be, for example, that navigation interventions to connect patients to resources such as food, housing, and financial assistance (e.g., McQueen et al., 2019) would be a more effective way to improve QoL during active treatment and into long-term survivorship, or that such interventions could be used in conjunction with health communication tools including narratives. Given structural racism and other social, economic, and political factors that perpetuate health inequities in the United States, it is also important to advocate for upstream policy interventions (e.g., economic development, housing policy, universal healthcare) that can improve social determinants of health and potentially lead to downstream improvements for multiple health outcomes (Hudson, 2019; Link and Phelan, 2015; Roberts, 2011).

This study has several strengths. Our novel, culturally targeted video narrative intervention for African American breast cancer patients had been pilot tested and shown to be acceptable and feasible (Pérez et al.,, 2014), and participants used it for over four hours on average. Findings add to the literature about QoL in African American breast cancer patients, a population for which cancer survivorship information has been limited, and shows that QoL is dynamic in the two years after a breast cancer diagnosis. Participants’ QoL was assessed five times over the two years after diagnosis using a measure that covered multiple QoL domains. The retention rate was relatively high, with very little missing data, and analytic methods were used that allowed us to include participants with partially missing data in the analysis.

Limitations

Our findings must be interpreted in light of the characteristics of our study sample, the characteristics of the intervention, and the broader informational context. As a group, nearly all study participants had the advantage of receiving care at a National Cancer Institute-designated Comprehensive Cancer Center, but most were also lower income. In addition, most participants had early-stage cancer and came from one geographic region in the Midwest. Thus, our findings might not be generalizable to other geographic areas or treatment facilities, or to samples with metastatic cancer or higher SES. Videos included in this intervention did not change over time, which might explain the decline in use at the second and third exposures (Pérez et al., 2020). In addition, the digital landscape for patients has changed considerably in the time since data collection for this study began. When our intervention was developed, cancer survivors who were racial/ethnic minorities were known to be underrepresented in survivor stories online (Eddens et al., 2009). If online resources for the general population have increased, African American women currently undergoing breast cancer treatment might have more online support options than were available to our study participants.

Conclusion

Although well-received by African American women with breast cancer in our sample, this intervention did not improve their QoL over the 2-year study. Because most watched videos pertained to topics of immediate interest to newly diagnosed patients (Pérez et al., 2020), additional work is needed to develop a more nuanced picture of particular intervention content and delivery contexts in which narratives may be an effective health-communication strategy for interventions aimed at improving QoL in African American women with breast cancer. The low QoL scores reported by study participants emphasize the urgent need to continue to seek ways to improve QoL and other health outcomes in this population.

Supplementary Material

Online Supplement 1
Online Supplement 2

Acknowledgements:

This research was funded by a grant from the National Cancer Institute (P50 CA095815, PI: M. Kreuter) and the National Cancer Institute Cancer Center Support Grant to the Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine in St. Louis, Missouri (P30 CA091842; PI: T. Eberlein) for services provided by the Health Behavior, Communication and Outreach Core. Dr. Thompson was supported in part by a Mentored Research Scholar Grant from the American Cancer Society (MRSG-19-086-01-CPPB, PI: Thompson). We thank our patient participants, the interviewers, and Ms. Lori Grove in Oncology Data Services at Washington University School of Medicine for assistance with medical record data collection. We greatly appreciate the physicians who helped recruit their patients for this study, including Drs. Timothy Eberlein, William Gillanders, Rebecca Aft, and Amy Cyr at Washington University School of Medicine and Dr. Theresa Schwartz and Ms. Pam Hunborg, RN, at Saint Louis University School of Medicine. The study CONSORT diagram (Figure 1) was used with permission from the publisher, Oxford University Press.

Footnotes

Trial registration: ClinicalTrials.gov identifier: NCT00929084

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